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An Optimal Seed Based compression algorithm for DNA Sequences

Advances in Bioinformatics 2016年第1期2016卷 3528406页

作者： Eric, Pamela Vinitha Gopalakrishnan, Gopakumar Karunakaran, Muralikrishnan Department of Information Science and Engineering Rajiv Gandhi Institute of Technology Bangalore 560032 India Department of Computer Science and Engineering National Institute of Technology Calicut Kerala 673601 India

This paper proposes a seed based lossless compression algorithm to compress a DNA sequence which uses a substitution method that is similar to the LempelZiv compression scheme. The proposed method exploits the repetition structures that are inherent in DNA sequences by creating an offline dictionary which contains all such repeats along with the details of mismatches. By ensuring that only promising mismatches are allowed, the method achieves a compression ratio that is at par or better than the existing lossless DNA sequence compression algorithms. © 2016 Pamela Vinitha Eric et al.

关键词： DNA sequencing compression algorithm Data compression compression Substitution method Nucleic acid sequence

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Research on Mine Belt Image compression and Transmission algorithm 8

Research on Mine Belt Image Compression and Transmission Alg...

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8th International Symposium on Computational Intelligence and Design (ISCID)

作者： Gao, Rui Miao, Changyun Li, Jie Yang, Yanli Tianjin Polytech Univ Sch Mech Engn Tianjin Peoples R China Tianjin Chengjian Univ Sch Control & Mech Engn Tianjin Peoples R China Tianjin Polytech Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781467395878

On-line damages detection of mine conveyor belt is developed by using machine vision technology. By analyzing the feature of images collected by the CCD camera for the Mine Conveyer Belt, an algorithm of JPEG encoding based on linear difference is proposed for compressing and transmission, which solves the problem of high efficiency and real-time transmission of image data. A method based on the parameter test is proposed in the algorithm for transmission error control. The algorithm can effectively reduce the amount of data transmission, and can ensure the real-time performance of the network, which has important application value in the detection system based on machine vision.

关键词： machine vision compression algorithm JPEG compression ratio

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Multistate Satellite System Reliability Optimization Based on Improved compression Inference algorithm and Bayesian Network

Multistate Satellite System Reliability Optimization Based o...

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IEEE Congress on Evolutionary Computation (IEEE CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Zheng, Xiaohu Chen, Xianqi Yao, Wen Chen, Xiaoqian Yang, Longqi Luo, Yazhong Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha Hunan Peoples R China Chinese Acad Mil Sci Natl Innovat Inst Def Technol Beijing Peoples R China

ISBN: (纸本)9781509060177

No doubt that the proper design of satellite system reliability is one of the most important issues in satellite system engineering. In order to optimize the satellite reliability, the reliability optimization method is studied in this paper based on compression algorithm, Bayesian Network (BN) and Particle Swarm Optimization (PSO). Firstly, the improved compression inference algorithm (ICIA) is proposed to model the BN reliability model of multistate system based on the existing compression and inference algorithms. Then, the reliability optimization problem is formulated, which is a typical discrete optimization problem with the discrete reliability measured in the number of each component's units as design variables. The process of optimization, based on the BN reliability model of multistate satellite system will be achieved by PSO. The efficacy of the proposed method is demonstrated in a microsatellite system reliability optimization, which verifies the importance of satellite reliability optimization in decreasing the cost of satellite development.

关键词： multistate satellite reliability optimization Bayesian Network compression algorithm Particle Swarm Optimization

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Complex Satellite Lifetime Optimization Based on Bayesian Network Reliability compression Inference algorithm

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IEEE ACCESS 2019年 7卷 175166-175185页

作者： Zheng, Xiaohu Yao, Wen Xu, Yingchun Chen, Xiaoqian Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Peoples R China Chinese Acad Mil Sci Natl Innovat Inst Def Technol Beijing 100071 Peoples R China

In the satellite lifetime optimization, reliability is a critical issue. For the complex satellite system, Bayesian network (BN) is an important method for reliability modeling and inference. As the number of system's components increases dramatically, the memory storage requirements of the system's node probability table (NPT) will exceed the computer's random access memory (RAM). To solve this challenge, compression methods have been proposed to reduce the memory storage requirements of NPT. However, for the complex satellite system with extreme large number of components and the explosion of probable state combination, the existing methods still face big challenge in compression efficiency. Therefore, an improved encoding compression algorithm is proposed to further enhance the NPT compression effect in this paper. For the hierarchical complex satellite system that has multiple subsystems which are further composed of multiple components, the multilevel BN reliability model is first constructed based on the proposed encoding compression algorithm. By the variable elimination algorithm, a multilevel BN reliability inference algorithm is proposed to perform the inference of the multilevel BN reliability model. Based on the basis of the reliability model above, further considering system mass, power and cost requirement, the satellite lifetime is properly designed by optimizing the system component configuration, including component model/type selection and number determination for redundancy. Finally, two cases are studied to demonstrate and validate the proposed algorithms.

关键词： Bayesian network complex satellite system compression algorithm lifetime optimization reliability

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49-4: A Low-power Reflective LCD System with Adaptive compression algorithm of Grey Scale

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SID Symposium Digest of Technical Papers 2018年第1期49卷

作者： Feng Long Yu Zhang Zongze He Lingyu Sun Xiuyun Chen Dkyoon Ming Chen Shuo Li Jianguang Yang Liang Zhang Zhenghua Lu Yuxuan Chen Pin Xiao Fei Liang Tingxiu Hou Liyu Fang Jingjun Du Beijing BOE Optoelectronics Technology Co. Ltd Beijing China

A 1.28-inch 6-bit color low-power reflective LCD prototype has been developed by using low refresh rate system and memory-type pixel (MTP) structure. As there is an intrinsic problem for the MTP structure that large flat areas, and loss of detail become noticeable when original 8-bit RGB color is converted to 2-bit RGB color. An adaptive compression algorithm of grey scale has been developed to minimize the image deterioration, which enables to select an appropriate parameter according to the types of images and the position on the screen. By a specific function of RGB point-to-point gray-scale transformation, the picture shows better effect than the traditional processing method. The simulation and experimental results verify the effectiveness of the adaptive compression algorithm.

关键词： Memory-in-pixel system on panel compression algorithm

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15-1: A Novel compression algorithm Application for De-Mura Compensation of AMOLED Panel

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SID Symposium Digest of Technical Papers 2023年第1期54卷

作者： Yini Zuo Eunho Lee Kyoungwon Lee Changman Kim Fei Shang Haijun Qiu Chengdu BOE Optoelectronics Group Co. Ltd. Chengdu China

A novel compression algorithm was adopted to compress De-mura compensation data, and the compression process was described in detail. The compensation performance of 2x2 compression case is close to the original 2x2 case, and performs better than 4x4 compensation case with the same file size as it. Apart from that, the combination of De-mura and compression also performs the good compensation results at low gray as well as low display brightness. The better performance, small space occupancy and low power consumption were reached simultaneously, indicating the effective application of combination of compression algorithm and De-mura algorithm.

关键词： AMOLED De-Mura Compensation compression algorithm

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Heuristic genetic algorithm parameter optimizer: Making lossless compression algorithms efficient and flexible

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 272卷

作者： Wang, Weijie Chen, Wenhui Yan, Li Yang, Yanqing Zhao, Huihuang Hengyang Normal Univ Coll Comp Sci & Technol Hengyang 421002 Peoples R China Hengyang Normal Univ Hunan Prov Key Lab Intelligent Informat Proc & App Hengyang 421002 Peoples R China Hunan Univ Natl Engn Lab Robot Visual Percept & Control Techn Hengyang Peoples R China

The processing of large volumes of time series data across various fields presents significant challenges, particularly when it comes to effectively managing floating-point numbers. Current dual precision floatingpoint lossless compression algorithms often struggle to deliver exceptional performance on diverse datasets, highlighting their inherent limitations. To address this issue, we propose a novel method called the Heuristic Genetic algorithm Parameter Optimizer for Lossless compression of Time Series Floating Point Data (HGAACTF). This method features a highly effective parameter optimizer designed specifically for compression algorithms that utilize leading zeros. The combination of our parameter optimizer and the HGA-ACTF algorithm strategy has been proven to outperform existing leading compression algorithms across multiple fields. This approach not only enhances the compression ratio but also significantly reduces both compression and decompression times. In our comparative study, we evaluated the HGA-ACTF algorithm against eleven well- performing algorithms and a variant of the algorithm, integrating our parameter optimizer and algorithmic strategy into other adaptable algorithms, and demonstrating notable improvements. Experimental results indicate that the HGA-ACTF algorithm achieves an average compression ratio improvement of 38.87%, with some datasets showing improvements of up to 54.36%. Our approach effectively addresses the transmission and storage of time series data, significantly reducing the overhead associated with data processing. The code can be found at https://***/wwj10/HGA-ACTF.

关键词： Time series floating point data Lossless compression Internet of things compression algorithm Heuristic genetic algorithm

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A parallel decoding algorithm for LZ2 data compression

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PARALLEL COMPUTING 1995年第12期21卷 1957-1961页

作者： DeAgostino, S Computer Science Department University ‘La Sapienza’ Via Salaria 113 00198 Rome Italy

The LZ2 compression method is hardly parallelizable since it is known to be P-complete. In spite of such negative result, we show in this paper that the decoding process can be parallelized efficiently on an EREW PRAM... 详细信息

关键词： compression algorithm textual substitution decoding parallel algorithm

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compression of next-generation sequencing quality scores using memetic algorithm

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BMC BIOINFORMATICS 2014年第15-Sup期15卷 S10-S10页

作者： Zhou, Jiarui Ji, Zhen Zhu, Zexuan He, Shan Zhejiang Univ Coll Biomed Engn & Instrument Sci Hangzhou 310027 Zhejiang Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen City Key Lab Embedded Syst Design Shenzhen 518060 Peoples R China Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England

Background: The exponential growth of next-generation sequencing (NGS) derived DNA data poses great challenges to data storage and transmission. Although many compression algorithms have been proposed for DNA reads in NGS data, few methods are designed specifically to handle the quality scores. Results: In this paper we present a memetic algorithm (MA) based NGS quality score data compressor, namely MMQSC. The algorithm extracts raw quality score sequences from FASTQ formatted files, and designs compression codebook using MA based multimodal optimization. The input data is then compressed in a substitutional manner. Experimental results on five representative NGS data sets show that MMQSC obtains higher compression ratio than the other state-of-the-art methods. Particularly, MMQSC is a lossless reference-free compression algorithm, yet obtains an average compression ratio of 22.82% on the experimental data sets. Conclusions: The proposed MMQSC compresses NGS quality score data effectively. It can be utilized to improve the overall compression ratio on FASTQ formatted files.

关键词： Quality Score compression Ratio Memetic algorithm compression algorithm Fitness Evaluation

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Bootstrap Analysis of compression algorithms

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IEEE LATIN AMERICA TRANSACTIONS 2020年第9期18卷 1639-1645页

作者： Beserra, Antonio A. R. Souza, Leandro C. Souza, Daniel F. L. Univ Sao Paulo Sao Carlos SP Brazil Univ Fed Paraiba Joao Pessoa Paraiba Brazil Univ Fed Rural Semi Arido Mossoro RN Brazil

compression algorithms have been proposed with the technology advance. However, there are not objective analysis procedures to guide a future choice of an algorithm directed for the type of data in the system they are intended for. This paper introduces a statistical framework, based on the bootstrap method, to execute the analysis of compression algorithms using an objective comparison parameter as a criterion. A case study using the compression ratio as the parameter and file samples of 4 different types was analyzed. The proposed scheme allowed us to infer which algorithm is better to be used for each data type. RLE has proven more suitable to image, audio and video files with Huffman obtaining comparable performance. For text files, LZW has remarkably outperformed all other algorithms.

关键词： Image coding Media Encoding compression algorithms Transform coding Security IEEE transactions compression algorithm Statistical Analysis Bootstrap

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